International News :-Artificial Intelligence and Cybersecurity: Attacking and Defending

Artificial Intelligence and Cybersecurity: Attacking and Defending

Knowledge base Cybersecurity is a manpower constrained market – therefore, the opportunities for artificial intelligence (AI) automation are vast. Frequently, AI is used to make certain defensive aspects of cyber security more wide-reaching and effective. Combating spam and detecting malware are prime examples.

On the opposite side, there are many incentives to use AI when attempting to attack vulnerable systems belonging to others. These incentives include the speed of attack, low costs and difficulties attracting skilled staff in an already constrained environment.

Current research in the public domain is limited to white hat hackers employing machine learning to identify vulnerabilities and suggest fixes. At the speed AI is developing, however, it won’t be long before we see attackers using these capabilities on a mass scale, if they don’t already.

How do we know for sure? The fact is that it is quite hard to attribute a botnet or a phishing campaign to AI rather than a human. Industry practitioners, however, believe that we will see an AI-powered cyber-attack within a year; 62% percent of surveyed Black Hat conference participants seem to be convinced in such a possibility.

Many believe that AI is already being deployed for malicious purposes by highly motivated and sophisticated attackers. It’s not at all surprising given the fact that AI systems make an adversary’s job much easier.

Why? Resource efficiency point aside, they introduce psychological distance between an attacker and their victim. Indeed, many offensive techniques traditionally involved engaging with others and being present, which, in turn, limited attacker’s anonymity. AI increases the anonymity and distance. Autonomous weapons are the case in point; attackers are no longer required to pull the trigger and observe the impact of their actions.

It doesn’t have to be about human life, either. Let’s explore some of the less severe applications of AI for malicious purposes: cybercrime.

Social engineering remains one of the most common attack vectors. How often is malware introduced in systems when someone just clicks on an innocent-looking link?

The fact is, to entice the victim to click on that link, quite a bit of effort is required. Historically, it’s been labour-intensive to craft a believable phishing email. Days and sometimes weeks of research and the right opportunity were required to successfully carry out such an attack. Things are changing with the advent of AI in cyber.

Analyzing large data sets helps attackers prioritize their victims based on online behavior and estimated wealth. Predictive models can go further and determine the willingness to pay the ransom based on historical data and even adjust the size of pay-out to maximize the chances and, therefore, revenue for cyber criminals.

Imagine all the data available in the public domain, as well as previously leaked secrets, through various data breaches are now combined for the ultimate victim profiling in a matter of seconds with no human effort.

When the victim is selected, AI can be used to create and tailor emails and sites that would be most likely clicked on based on crunched data. Trust is built by engaging people in longer dialogues over extensive periods of time on social media which require no human effort. Chatbots are now capable of maintaining such interaction and even impersonate the real contacts by mimicking their writing style.

Machine learning used for victim identification and reconnaissance greatly reduces attacker’s resource investments. Indeed, there is even no need to speak the same language anymore! This inevitably leads to an increase in scale and frequency of highly targeted spear phishing attacks.

The sophistication of such attacks can also go up. Exceeding human capabilities of deception, AI can mimic voice thanks to the rapid development in speech synthesis. These systems can create realistic voice recordings based on existing data and elevate social engineering to the next level through impersonation. This, combined with other techniques discussed above, paints a rather grim picture.

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